Systems and methods for assessing protection needs of retirement services clients and determine cross-selling potential of customers

1. A computer-implemented method comprising: executing, by a server, an analytical model using a K-nearest neighbor collaborative filtering technique to select a first subset of a set of users; collecting, by the server, a set of data records associated with the first subset of users by scanning at least one social networking database and at least one internal database; determining, by the server using the data scanned from the at least one social networking database and the internal database, one or more characteristics associated with each user within the first subset of users; determining, by the server using the data scanned from the at least one social networking database and the internal database, a first value corresponding to a life insurance or retirement product need for each user within the first subset of users; generating, by the server, a multi-dimensional matrix corresponding to a propensity for purchasing at least one selected life insurance or retirement product that satisfies the life insurance or retirement product need for each user within the first subset of users, wherein the server assigns a second value to each user within the first subset of users based on the respective user's determined propensity for purchasing the at least one selected life insurance or retirement product, and wherein each user is positioned within the multi-dimensional matrix in accordance with the respective user's assigned first and second values; selecting, by the server based on a relative position of each user within the multi-dimensional matrix, a second subset of users that have a highest value of correlation between the first and the second values, the second subset of users corresponding to users with a highest correlation between the propensity of purchasing and life insurance or retirement product needs; automatically generating, by the server, a customized electronic mail for each user within the second subset of users, the electronic mail comprising a hyperlink corresponding to an automated transaction platform website displaying the at least one selected life insurance or retirement product in accordance with the life insurance or retirement product need for each user within the second subset of users and based upon the propensity for purchasing the at least one selected life insurance or retirement product for each user within the second subset of users; transmitting, by the server, the electronic mail to a computing device associated with each user within the second subset of users; and training, by the server using a stochastic gradient descent algorithm, the analytical model for future life insurance or retirement product analysis.

2. The method according to claim 1 , further comprising: continuously monitoring, by the server, electronic activities associated with each user within the second subset of users.

3. The method according to claim 1 , further comprising: automatically initiating, by the server, a phone session with at least one user within the second subset of users.

4. The method according to claim 1 , wherein each data record comprises information including demographics, professional background, medical history, and financial history.

5. The method according to claim 1 , further comprising: calculating, by the server, an amount of life insurance for each of the users within the first subset of users based on data in the internal database.

6. The method according to claim 5 , wherein the data in the internal database includes at least one of income, amount of debt, number of family dependents, savings, and monthly family expenditure.

7. The method according to claim 5 , wherein calculating the amount of life insurance comprises determining a trend in inflation.

8. The method according to claim 5 , wherein calculating the amount of life insurance comprises determining a trend in interest rates.

9. The method according to claim 5 , wherein the data comprises at least one of age, gender, postal code, occupational background, monthly expenditures, income, retirement plan, medical history, and marital status.

10. The method according to claim 1 , further comprising: calculating, by the serve for each user within the second subset of users, a lump sum required to fund an annuity.

11. The method according to claim 1 , wherein the propensity determined by the server comprises estimating the propensity at a plurality of predicted life events.

12. The method according to claim 11 , wherein the plurality of predicted life events include at least one of birth of a child, birthday, marriage, accidents, diseases, and death of a relative.

13. The method according to claim 1 , further comprising automatically granting, by the server, access to the automated transaction platform website for each user within the second subset of users to purchase the at least one selected life insurance or retirement product.

14. The method according to claim 1 , further comprising tracking, by the server, users in the subset of the set of users that have purchased the at least one selected life insurance or retirement product.

15. The method according to claim 1 , further comprising automatically generating, by the server, correspondence to each user in the subset of the set of users based on a renewal.